Fix CLAP converting script (huggingface#27153)

* update converting script

* make style

src/transformers/models/clap/convert_clap_original_pytorch_to_hf.py

@@ -16,8 +16,7 @@
 import argparse
 import re
 
-import torch
-from CLAP import create_model
+from laion_clap import CLAP_Module
 
 from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
 
@@ -38,17 +37,25 @@
 processor = AutoFeatureExtractor.from_pretrained("laion/clap-htsat-unfused", truncation="rand_trunc")
 
 
-def init_clap(checkpoint_path, enable_fusion=False):
-    model, model_cfg = create_model(
-        "HTSAT-tiny",
-        "roberta",
-        checkpoint_path,
-        precision="fp32",
-        device="cuda:0" if torch.cuda.is_available() else "cpu",
+def init_clap(checkpoint_path, model_type, enable_fusion=False):
+    model = CLAP_Module(
+        amodel=model_type,
         enable_fusion=enable_fusion,
-        fusion_type="aff_2d" if enable_fusion else None,
     )
-    return model, model_cfg
+    model.load_ckpt(checkpoint_path)
+    return model
+
+
+def get_config_from_original(clap_model):
+    audio_config = {
+        "patch_embeds_hidden_size": clap_model.model.audio_branch.embed_dim,
+        "depths": clap_model.model.audio_branch.depths,
+        "hidden_size": clap_model.model.audio_projection[0].in_features,
+    }
+
+    text_config = {"hidden_size": clap_model.model.text_branch.pooler.dense.in_features}
+
+    return ClapConfig(audio_config=audio_config, text_config=text_config)
 
 
 def rename_state_dict(state_dict):
@@ -94,14 +101,14 @@ def rename_state_dict(state_dict):
     return model_state_dict
 
 
-def convert_clap_checkpoint(checkpoint_path, pytorch_dump_folder_path, config_path, enable_fusion=False):
-    clap_model, clap_model_cfg = init_clap(checkpoint_path, enable_fusion=enable_fusion)
+def convert_clap_checkpoint(checkpoint_path, pytorch_dump_folder_path, config_path, model_type, enable_fusion=False):
+    clap_model = init_clap(checkpoint_path, model_type, enable_fusion=enable_fusion)
 
     clap_model.eval()
-    state_dict = clap_model.state_dict()
+    state_dict = clap_model.model.state_dict()
     state_dict = rename_state_dict(state_dict)
 
-    transformers_config = ClapConfig()
+    transformers_config = get_config_from_original(clap_model)
     transformers_config.audio_config.enable_fusion = enable_fusion
     model = ClapModel(transformers_config)
 
@@ -118,6 +125,9 @@ def convert_clap_checkpoint(checkpoint_path, pytorch_dump_folder_path, config_pa
     parser.add_argument("--checkpoint_path", default=None, type=str, help="Path to fairseq checkpoint")
     parser.add_argument("--config_path", default=None, type=str, help="Path to hf config.json of model to convert")
     parser.add_argument("--enable_fusion", action="store_true", help="Whether to enable fusion or not")
+    parser.add_argument("--model_type", default="HTSAT-tiny", type=str, help="Whether to enable fusion or not")
     args = parser.parse_args()
 
-    convert_clap_checkpoint(args.checkpoint_path, args.pytorch_dump_folder_path, args.config_path, args.enable_fusion)
+    convert_clap_checkpoint(
+        args.checkpoint_path, args.pytorch_dump_folder_path, args.config_path, args.model_type, args.enable_fusion
+    )